Our overall goal is to demonstrate within two years human closed-loop control of the DARPA Revolutionizing Upper Limb Prosthesis, based on real-time decoding of electrocorticographic (ECoG) signals. Under visual feedback, our human subjects will achieve sufficient cortical control of the prosthesis to reach out, grasp, and manipulate real objects. Our collaborative team will build on its substantial experience in developing and testing neural control algorithms for the Modular Prosthetic Limb (MPL, developed by JHU- APL), which arose from participation in the DARPA-sponsored RP2009 program. Based on our unique combination of expertise and experience, we are poised to meet the RFA's Grand Challenge with an innovative approach using parallel experiments in human subjects and in animals. While we develop and test ECoG- based neural control algorithms in patients implanted for the clinical aims of epilepsy surgery, parallel studies in animals will afford more consistent and long-term experimental time to validate the control algorithms, and allow deeper investigation into electrode placement and configuration, including investigating the relationship between intra-cortically recorded spikes and local field potentials (LFPs) and surface-recorded ECoG. We will test the hypothesis that both open- and closed-loop control of the prosthetic limb can be achieved using ECoG spectral features at different time and frequency scales, e.g. low frequencies for slow and/or coarse movements and high frequencies (>70 Hz) for rapid and/or individuated movements. Based on these features, subjects will use the prosthetic limb to perform a center-out reach task in 3D space with coordinated grasping of objects requiring different hand conformations that incorporate both wrist and 5 finger actions. Brain control will be implemented with real-time signal processing of ECoG and actuation of the prosthetic limb under closed-loop visual feedback of object-targeted limb movements. Closed-loop control will be first demonstrated using a virtual reality model of the prosthetic limb and subsequently using the JHU-APL modular prosthetic limb itself. Outcomes will be assessed with measures of success rate, time to trial completion, trajectory/grasp-shape similarity to native limb movements, and overall learning/adaptation rate. PUBLIC HEALTH RELEVANCE: Project Narrative This project will demonstrate the feasibility of using the signals recorded from non-penetrating electrodes on the surface of the brain to allow patients who have lost arm and/or hand function to intuitively control a revolutionary new prosthetic limb with far greater versatility and life-like dexterity than previously available prostheses. This could have a profound long-term impact on the ability of future generations of patients seeking to restore lost upper limb function with a lifelike prosthesis.